1. Introduction to Pivots
Pivots provide a deeper layer of analysis by breaking down metrics to showcase how data is spread across specific properties or options. This enables users to view metrics in a more granular fashion, offering clearer insights.
To comprehend the utility of pivots, one needs to first understand how metrics are constructed in RevBI. As an example, consider a metric that calculates the total amount committed in a given quarter:
This metric might utilize the 'opportunity' object, applying an aggregation function.
It aggregates, or sums up, the amount column within the 'opportunity' object.
Further refinement can be applied using conditions, such as filtering deals based on forecast categories like 'commit'.
While the metric provides a single cumulative figure, for a more detailed perspective, such as commitments by each salesperson, pivots become invaluable.
2. Using a Pivot
Pivots allow for a more refined view of a metric data distribution:
A single-value metric can be transformed using a pivot to display its distribution across parameters like different users.
Fields accessible in the record list used for metric calculations can be utilized for pivots. For example, breaking down a metric by 'username' provides insights into each user's contribution to the overall value.
The beauty of pivots lies in their ability to layer analysis:
You can pivot by different fields, like 'creation date', to see metrics spread month-over-month.
For deeper granularity, RevBI supports a second pivot. Post breaking down by 'creation date', you can further pivot by 'username' to discern individual contributions within each month.
In the following example, we are going to apply two pivots to our “Commit” metric. In your widget, select the metric of your choice, then under “Pivot”, select “Opportunity - Close Date Q-o-Q”.
As a final step, try adding a second pivot. In our example, we selected “Opportunity - Opportunity Stage” to understand in which stages our Commit deals are across each quarter. If you feel adventurous, try changing the Pivot Visualization at the right corner of your metric. For instance, change it from the “stacked bar” visualization to a “table” visualization.
Pivots enhance data visualization in RevBI by enabling metrics to be dissected based on specific properties. With the capacity to use up to two pivots, users gain substantial flexibility in their data analysis within widgets.
4. Finalizing and Using Widgets
After configuring the widget to your satisfaction, save it.
These saved widgets can then be seamlessly integrated into dashboards within RevBI, enhancing your overall data visualization experience.
RevBI widgets are designed to be a powerful tool, providing users with customizable and detailed insights, which in turn facilitates informed decision-making.